What are the runtime requirements?
Python 3.x, Django (version supported shown on PyPI), and optionally Django Rest Framework for DRF tool integration. No additional infrastructure changes needed.
@omarbenhamid
基本信息
Django MCP Server is a Django extensions to easily enable AI Agents to interact with Django Apps through the Model Context Protocol it works equally well on WSGI and ASGI
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"django-mcp-server": {
"command": "python",
"args": [
"manage.py",
"mcp_inspect"
]
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。
Django MCP Server is an implementation of the Model Context Protocol (MCP) for Django. It enables MCP clients and AI agents to interact with any Django application by exposing Django models and custom logic as MCP tools through a declarative, Django-style interface.
Install via pip (pip install django-mcp-server), add mcp_server to INSTALLED_APPS, include its URLs in your project’s urls.py, then define tools by subclassing ModelQueryToolset or MCPToolset in a mcp.py file. The MCP endpoint is served at /mcp by default. Use python manage.py mcp_inspect to verify tool declarations.
MCPToolset.Python 3.x, Django (version supported shown on PyPI), and optionally Django Rest Framework for DRF tool integration. No additional infrastructure changes needed.
Set `DJANGO_MCP_AUTHENTICATION_CLASSES` in `settings.py` to use DRF authentication classes. For production or public data, consider OAuth2 integration with django-oauth-toolkit and its DCR add-on.
Yes, it works on both WSGI and ASGI without any infrastructure changes. The server manages state independently of the deployment model.
Yes, use `drf_publish_create_mcp_tool`, `drf_publish_update_mcp_tool`, `drf_publish_delete_mcp_tool`, or `drf_publish_list_mcp_tool` annotations or method calls on your DRF views. Note that built-in authentication and pagination are disabled when used this way.
Use the management command `python manage.py mcp_inspect` to list declared tools. You can also connect with the MCP Python SDK via `streamablehttp_client` or test in Claude Desktop using a stdio configuration.

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